Human computer interaction (HCI) has gained widespread attention because it creates the possibility of users' interacting with computers and environments. Among all input pathways, electrooculography (EOG)-based systems [1-7] show great potential for controlling computers and devices by recognizing the user's eye movements, which is of particular significance to people with disabilities requiring hands-free alternatives (e.g., paralyzed or “locked-in” patients).
Electrooculography (EOG/E.O.G.) is a technique for estimating eye lateral based on changes in the inferred axis of the corneo-retinal dipole, with the retina having a negative potential. To measure eye movement, pairs of electrodes may be placed above and below or to the eye or to the left and right of the eye. The resting potential may vary based on illumination. Drift of the measured DC baseline potential and inferred axis of the eye. This can be compensated by periodic calibration, or analysis of the EOG signal for movements rather than position. Calibration can be achieved by simply having the user look forward, left and right, up and down, to set the center and range of the signal.
Some literature applies this label to analysis of electromyographic signals emitted by eye muscles. Note that the EMG signals reveal the activation of the muscle fiber action potentials, and are present as an alternating current signal whose amplitude and frequency spectrum characteristics may vary depending on eye movement, while the dipole measurement of the corneo-retinal dipole is a direct current measurement related to eye position.
Various efforts have been applied for implementing an EOG controlled human computer interface.
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